🧅 Applied Example: Designing Disaster Risk Research Using Saunders’ Onion Framework

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 🧅 Applied Example: Designing Disaster Risk Research Using Saunders’ Onion Framework

🧪 Case Study 1: Early Warning Systems (EWS) in Rasuwa District

📌 Research Title:

"Evaluating the Effectiveness of Flood Early Warning Systems in Rasuwa District: A Mixed-Methods Study"

This case explores how Saunders' Onion can guide a research design focused on assessing the performance and perception of flood early warning systems (EWS) in a hazard-prone district of Nepal.

🧠 1. Research Philosophy: Pragmatism

Justification:
The researcher combines two types of knowledge:

  • Quantitative (Positivist): Objective measures of EWS performance, such as how fast alerts were sent and how many people received them.

  • Qualitative (Interpretivist): Community perceptions—whether locals trusted the alert, how they reacted, and what cultural or social factors influenced their response.

Pragmatism allows this combination, focusing on what works best to answer the research questions.

Data Examples:

  • Quantitative: Timeliness of alerts (in minutes), percentage of households receiving alerts.

  • Qualitative: Focus group discussions (FGDs) on perceived usefulness and trust in the system.

🧭 2. Research Approach: Deductive

Justification:
The study tests a theory drawn from global DRR frameworks, particularly:

Theory: Timely EWS alerts reduce flood-related fatalities.
(Based on UNISDR / Sendai Framework)

The researcher starts with this theory and collects data to confirm or challenge it in the local context.

🧰 3. Methodological Choice: Mixed Methods

Justification:
The topic demands both statistical insight (how well the system worked) and human insight (how people perceived and reacted to it).

Methods:

  • Quantitative: A structured household survey with 200 participants, containing 30 closed-ended questions.

  • Qualitative: 5 Key Informant Interviews (KIIs) with disaster management officials, such as municipality leaders and Red Cross personnel.

🧩 4. Research Strategy: Survey + Case Study

Justification:
The researcher uses two strategies in combination:

  • Survey: Administered using digital tools like KoboToolbox for efficiency in data collection and remote areas.

  • Case Study: Focused investigation of the 2021 flood event in Rasuwa, to understand EWS performance in a real scenario.

⏳ 5. Time Horizon: Cross-Sectional

Justification:
The study collects data at one point in time—specifically, after the 2023 flood season—to capture experiences and system performance in that context.

🧮 6. Data Collection and Analysis Techniques

Quantitative:

  • Descriptive statistics using SPSS: Frequencies, percentages, mean alert times.

Qualitative:

  • Thematic analysis using NVivo: coding participant narratives for key themes such as trust, barriers to response, and local adaptation.

🏛️ Case Study 2: Local Government DRRM Effectiveness

📌 Research Title:

"Assessing Local Governance in Disaster Risk Reduction: Evidence from Nepal’s Federal Transition"

This example focuses on evaluating how local governments have adapted to their new DRRM roles under federalism.

🧠 1. Research Philosophy: Pragmatism

Justification:
To understand both structural and lived realities, the study blends:

  • Positivist: Assessment of institutional performance using measurable indicators.

  • Interpretivist: Exploration of how local communities experience and perceive DRRM under the new federal structure.

🧭 2. Research Approach: Inductive

Justification:
Unlike the previous case, this study doesn't start with a pre-existing theory but aims to build one based on what the data reveals.

For example, it may generate new insights into how federalism affects coordination or local DRR leadership.

🧰 3. Methodological Choice: Mixed Methods

Justification:
The research requires institutional data and community voice.

Methods:

  • Quantitative: Analysis of DRR budget allocation percentages and policy compliance checklists across municipalities.

  • Qualitative: Three Focus Group Discussions (FGDs) with vulnerable groups such as women, elderly, and persons with disabilities.

🧩 4. Research Strategies: Survey + Case Study 

Justification:
The researcher uses multiple sources to validate findings and increase reliability:

  • Document Review: Policy documents, DRRMA 2017 implementation reports.

  • Interviews: 10 semi-structured interviews with local officials, planners, and DRR focal points.

⏳ 5. Time Horizon: Longitudinal

Justification:
The study tracks local DRRM efforts over time—spanning from 2017 (the year the DRRMA was passed) to 2023—making it possible to observe trends, delays, and shifts in capacity.

🧮 6. Data Collection and Analysis Techniques

Quantitative:

  • Trend analysis of DRRM policy implementation using Excel.

Qualitative:

  • Critical Discourse Analysis: Examines how local officials speak about roles, responsibilities, and challenges—offering insights into power dynamics, institutional confusion, and resource constraints.

📝 Takeaway for Students

These two examples show how each layer of Saunders’ Onion helps you make informed design choices—from your philosophical position down to the specific tools you use. Importantly, research in disaster contexts often benefits from pragmatic thinking and mixed methods, because real-world problems rarely fit into neat methodological boxes.

🌟 Tip: When planning your dissertation, try mapping it out using this same layer-by-layer approach. You’ll not only gain clarity but also be better prepared to justify your design in front of your supervisor or committee.


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